Because hit-and-run crashes account for a significant share of pedestrianfatalities, a better understanding of these crashes will assist efforts to reduce pedestrian fatalities. Of the more than 48,000 pedestrian deaths that were recorded in the United States between 1998 and 2007 (Fatality Accident Reporting System [FARS]), 18.1percent of them were the victims of hit-and-run crashes, and the percentage of fatal pedestrian hit-and-runs has been rising as the number of all pedestrian fatalities has decreased. Using FARS data on single pedestrian fatal victim crashes between 1998-2007,logistic regression analyses were conducted to identify factors related to hit-and-run and to identify factors related to the identification of thehit-and-run driver. Results indicate an increased risk of hit-and-run in the early morning, during non-daylight, and on the weekend. Results also indicate that certain driver demographic characteristics (young, male), behavior (notably alcohol use), and history (e.g., suspended license or history of DWI/DUI convictions) are associated with hit-and-run. There also appears to be an association between the type of victim and the likelihood ofthe driver being identified. Alcohol use and early morning, the time frame when persons may be leaving bars, were among the leading factors that increased the risk of hit-and-run. Reducing alcohol-related crashes could substantially reduce pedestrian fatalities as a result of hit-and-run. Driver characteristics will assist in the development of countermeasures, however, more information about this population may be necessary.
Abstract